Artificial Intelligence and Cybercriminals: Five Ways Artificial Intelligence Can Be Used to Prevent Cyber ​​Attacks

Authentication company Okta recently confirmed that its data has been hacked and businesses are on high alert. Okta is a company that provides authentication services to many large companies, including FedEx, Sonos, and T-Mobile. Ekta is not the only company that faces cyber attacks. Cybercrime poses a major threat to global prosperity in the fourth industrial revolution. As these attacks increase in volume, artificial intelligence (AI) not only supports under-resourced analysts, but also provides a range of protection against malicious attacks. In this article from AI company Avir, we look at five ways AI can help prevent different types of cyber attacks. Join us in this article on artificial intelligence and cybercriminals.

Artificial intelligence and anti-spam and phishing

Phishing is a type of cyber attack in which the fraudster tries to deceive the victim by impersonating a person or company; Phishing is a major threat to businesses. Companies can build a system that can detect unusual behavior and anomalies by building algorithms on understanding and recognizing patterns from large amounts of data. Using data analysis and this algorithm, AI can identify spam and phishing emails by considering message content and context while looking for anomalies and warning signals.

DNS data protection with artificial intelligence

Many cybercriminals use the Domain Name System (DNS) to access valuable customer and business information. Machine learning (ML) and artificial intelligence can protect companies against these types of attacks by analyzing trillions of DNS queries to better understand where cybercriminals are hiding. DNS spoofing and poisoning occurs when an attacker intercepts a DNS request and sends a fake (poisoned) response to the client. This is a critical problem facing businesses as there are over 30,000 DNS poisoning attacks per day and 70% of all cyber attacks involve the DNS layer.

DNSFilter provides AI-based DNS security. DNS filtering solution blocks online threats and inappropriate content. This solution uses DNS to categorize and then block or allow access to various websites. DNS filtering is considered edge layer protection because it provides security at the outermost layer of security – the Internet.

DNS data protection with artificial intelligence

Using artificial intelligence to detect advanced malware

Malware is a growing threat to cybersecurity, but AI is empowering companies’ defense strategies to grow with it. Every malware sample that comes along makes the AI ​​stronger. Deep learning AI enables companies to optimize their malware protection strategies by increasing the quantity and accuracy of analyzed data.

Netskope, the leader in secure access services (SASE), has developed a comprehensive, multi-layered threat protection system for scanning its customers’ network traffic. The company uses artificial intelligence and machine learning to power multiple engines in fast inline scanning, as well as deep scanning based on static and dynamic analysis to help identify malware.

Artificial intelligence in the protection of authenticity

Authentication is central to cybersecurity, and the evolution toward multi-factor authentication (MFA) has helped secure access. As cybercriminals evolve their tactics, artificial intelligence will play an important role in improving authentication processes. Traditional authentication processes implement threat protection at the login stage, but AI systems can detect and respond to threats during the user session. For example, if a user suddenly moves to a new location and device, or tries to access financial information unrelated to their work, they will be asked to verify their identity.

Implementation risk-based authentication company OneLogin offers an authentication system called SmartFactor that is powered by artificial intelligence and streamlines login attempts in real-time, allowing users to act quickly and check for high-risk activity. , easily define risk thresholds and automatically adjust authentication requirements.

Artificial intelligence and predicting the risk of violating the law

Artificial intelligence systems have the ability to predict how and where organizations are most likely to break the law, so they can plan to allocate resources and tools toward weak points. Prescriptive insights from AI analytics can help organizations configure and improve controls and processes to effectively improve their cyber resilience.

SentinelOne, a pioneer in autonomous security, takes risk prediction one step further with its Watch Tower solution. The service extends visibility and action to new attacker techniques, global APT campaigns and emerging cybercrimes by realizing threats on an intelligence-driven platform.

And in the end that…

Artificial intelligence and machine learning play an important role in cyber security, enabling tasks such as data classification, data clustering, action recommendations, probabilistic fusion, and prediction. These two technologies can analyze large amounts of data to identify threats such as phishing and malware. In addition, they can track user behavior, detect unwanted actions, and react accordingly, stop threats in real-time without disrupting business processes, and discover data that might otherwise be detected. Humans run away.

Artificial intelligence has many applications in cybersecurity, including breach risk prediction, phishing detection, malware detection and prevention, user authentication, spam filtering, password protection, bot detection, behavioral analysis, segmentation, and network security. Fraud detection, dark web threat intelligence, incident response. , vulnerability management and identity and access management.

While AI has the potential to greatly improve cybersecurity, there are downsides to consider. Organizations need more resources and financial investments to build and maintain artificial intelligence systems. Acquiring diverse data sets for training these systems can also be time-consuming and costly. Insufficient data can lead to inaccurate results and false positives. In addition, cybercriminals can use artificial intelligence to carry out more sophisticated attacks.

As a result, AI is critical to enhancing IT security performance at scale. Artificial intelligence enables threat analysis and detection, helping security professionals minimize the risk of breaching the law, prioritize risks, create direct incident response, and detect malware attacks before they happen. Despite potential weaknesses, AI will continue to advance cybersecurity and improve organizations’ overall security systems.

If you intend to use artificial intelligence services and systems and are looking to deal with cybercriminals with the help of artificial intelligence, we at Avir Artificial Intelligence Company are by your side to provide you with the best services.

Get in touch with us!